Presentation by Thies Blokhuijsen (Deltares), Cees Voesenek (Vortech, Netherlands), at the Delft-FEWS International User Days, during Delft Software Days - Edition 2022. Wednesday, 9 November 2022.
Presentation by Thies Blokhuijsen (Deltares), Cees Voesenek (Vortech, Netherlands), at the Delft-FEWS International User Days, during Delft Software Days - Edition 2022. Wednesday, 9 November 2022.
DSD-INT 2022 Digital Twin - SALTISolutions - Voesenek
1.
Date: 09 November 2022
Digital Twin - SALTISolutions
Prototype of a Delft-FEWS based Digital Twin
Cees Voesenek (VORtech)
Thies Blokhuijsen (Deltares)
2.
What is VORtech?
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⚫ Developing scientific software
Including the development of mathematical models and algorithms for various
applications.
⚫ Accelerating and improving scientific software
By enhancing algorithms, using high performance computing, porting to modern
programming languages, and adding documentation.
⚫ Consultancy on scientific software
By identifying and analyzing the code and the corresponding algorithms and
underlying mathematical models.
⚫ Maintenance of scientific software
By using advanced software engineering tools.
⚫ Data science
Analytics, machine learning, time series analysis
3.
Outline
1. Introducing Digital Twins & SALTI Solutions
2. Digital Twin SALTI Solutions
3. Interactive Interface
4. Future developments
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5.
Research Programme towards understanding, forecasting and
finding solutions for salinization of the Dutch Delta
5
6.
What is a Digital Twin?
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Just a model?
A buzzword?
Introduced in manufacturing world:
− Product development
− Predictive maintenance
Wikipedia: “A digital twin is a virtual representation of a real-world
physical system or product that serves as the indistinguishable
digital counterpart of it for practical purposes, such as system
simulation, integration, testing, monitoring, and maintenance”
7.
What we think defines a Digital Twin
7
real physics
real data
charts
solitary
passive social
interactive
advanced
visualisation
toy physics
fabricated
data
real physics
social
interactive
advanced
visualisation real data
8.
Virtual Delta: final objective
Requirements:
• Based on physical processes
• Incorporating realistic measures, interventions and
developments
• Facilitate discussion on measures/interventions/estuarine
ambitions and invite interaction
• Based on real-time conditions
• Serves as an integrator of new knowledge and accelerator of
research
A digital twin of the delta for short, medium
and long term decision making.
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9.
real physics
social
interactive
advanced
visualisation real data
Prototype
Requirements:
• Recognizable system: Rhine-Meuse Delta
• Focussed on short-term
• Facilitate discussion towards end result
• MVP with architecture that can be build upon
• Real-time data
• Real interventions
• Interactive, non-expert interface
A digital twin of a delta for short, medium
and long term decision making.
A digital twin of the Rhine Meuse Delta for
short, medium and long term decision
making.
9
10.
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We are talking about the Rhine-Meuse Delta
Graphic from: Het verhaal van de Rijn-Maasmonding, platform Rivieren 2019
Lek (Rhine)
Waal (Rhine)
Meuse
11.
Prototype Architecture
1. Computing Engine: Delft-FEWS
2. Data Lake: Deltares Open Archive
3. API: FEWS Web Services
4. Interactive Interface: to be developed
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12.
Component 1: Delft-FEWS System
4 Windows FSS’s MC & Central DB Operator Client
Forecasts & observations
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13.
Delft-FEWS Config: Model
- 1D Sobek3
- Model forcing adjustable:
- Downstream waterlevel
- Upstream discharge
- Water inlets and water outlets
- Salinity on boundaries
- For prototype model with open barriers
- Model is scheduled every 6 hours
- Hindcast + Forecast (7 days)
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14.
Architecture
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Deltares Open Archive
• Document-oriented, NoSQL database
• Data is stored in an unstructured way
• All kinds of data can be stored
• Access to data through API
• High Delft-FEWS integration
• Storage of third party NetCDF files
Component 2
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16.
• Filestorage
• Open Archive Server
• FEWS Web Service
• Configured through xml
Simple set-up
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17.
Data & scenario results must be available as soon as possible!
Open Archive Developments
1. For data available on fixed times/intervals:
→ Specify Harvester interval per ExternalStorageId
2. For unpredictable (w.r.t. timing) data
→ Immediate harvester
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Configuration example
1)
2)
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Architecture
4 Windows FSS s n o i n
Fo s s o s ions
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Component 3: FEWS PI REST Web services
Through the API access of:
1. Delft-FEWS Client-Server System
Mainly to run the model(s)
2. Deltares Open Archive
To retrieve data
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FEWS PI REST Webservice API - Development
Most important: Post runtask extended with properties:
&property(fileName)=exportFile&property(outputValue)=9.0
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Architecture
4 Windows FSS s n o i n
Fo s s o s ions
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23.
Interactive interface for SALTI DT
• Requirements
− Should be usable by non-FEWS experts
− Allow exploring current measurement and simulation data
− Allow starting what-if scenarios
− Allow exploring and comparing the results of what-if scenarios
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Technology
• Web-based: cross-platform, no installation, instantly usable
• Front-end web application without dedicated back-end
− All rendering is done in the us ’s browser
− Data are retrieved from FEWS PI REST Web Service as JSON
− Needs only a simple web server and access to FEWS Web Services
• Uses Vue.js with Vuetify
− Rapid development with many pre-made components
− Same technology as WebOC
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25.
Exploring data
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FEWS PI endpoints:
• /locations
• /timeseries
26.
Starting what-if scenarios
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FEWS PI endpoints:
• /locations
• /timeseries
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Starting what-if scenarios
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FEWS PI endpoints:
• /runtask
• /taskrunstatus
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Exploring scenario results
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FEWS PI endpoints:
• /locations
• /timeseries
• /netcdfstorage
forecasts
• /taskruns
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Exploring scenario results
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FEWS PI endpoints:
• /attributes
• /parameters
• /locations
• /timeseries
• /netcdfstorage
forecasts
• /taskruns
30.
Exploring scenario results
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FEWS PI endpoints:
• /attributes
• /parameters
• /locations
• /timeseries
• /netcdfstorage
forecasts
• /taskruns
31.
On to a new scenario!
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FEWS PI endpoints:
• /locations
• /timeseries
32.
Future Developments
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Physics & models:
• 2D/3D and data-driven models, hybrid modelling
• Accelerate research: opening DT up for models in development.
• Salt intrusion around structures
Visualisation
• Representing 1D results spatially
• 2D/3D visualization
• Visualisation of structures and interventions
Increase immersiveness / interactiveness
• Through data driven modelling, hybrid modelling & batch forecasting
33.
Future Developments
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Real Data: Remote Sensing, Data on structures such as sluices
Increase number of interventions and freedom in scenario development
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